Vision. We train a ResNet18 [1]} encoder, trained on CIFAR10 (InD) [2]}, evaluated on unseen data from CIFAR10 (full semantic overlap), CIFAR100 (partial semantic overlap) [2]} and SVHN (no semantic overlap) [4]}. We also train a LeNet encoder on MNIST (InD) [5]}, and evaluate it on MNIST-like data i.e., unseen data from MNIST (full semantic overlap), FashionMNIST (no semantic overlap) [6]}, eMNIST (partial semantic overlap) [7]} and kMNIST (no semantic overlap) [8]} (collectively referred to as \(x\) -MNIST) datasets for digit classification as is typically reported in literature [9]}, [10]}.
